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2.  Increased cyclin D1 expression can mediate BRAF inhibitor resistance in BRAF V600E–mutated melanomas 
Molecular cancer therapeutics  2008;7(9):2876-2883.
Recent studies have shown that there is a considerable heterogeneity in the response of melanoma cell lines to MEK and BRAF inhibitors. In the current study, we address whether dysregulation of cyclin-dependent kinase 4 (CDK4) and/or cyclin D1 contribute to the BRAF inhibitor resistance of melanoma cells. Mutational screening identified a panel of melanoma cell lines that harbored both a BRAF V600E mutation and a CDK4 mutation: K22Q (1205Lu), R24C (WM39, WM46, and SK-Mel-28), and R24L (WM902B). Pharmacologic studies showed that the presence of a CDK4 mutation did not alter the sensitivity of these cell lines to the BRAF inhibitor. The only cell line with significant BRAF inhibitor resistance was found to harbor both a CDK4 mutation and a CCND1 amplification. Array comparative genomic hybridization analysis showed that CCND1 was amplified in 17% of BRAF V600E–mutated human metastatic melanoma samples, indicating the clinical relevance of this finding. As the levels of CCND1 amplification in cell lines are lower than those seen in clinical specimens, we overexpressed cyclin D1 alone and in the presence of CDK4 in a drug-sensitive melanoma line. Cyclin D1 overexpression alone increased resistance and this was enhanced when cyclin D1 and CDK4 were concurrently overexpressed. In conclusion, increased levels of cyclin D1, resulting from genomic amplification, may contribute to the BRAF inhibitor resistance of BRAF V600–mutated melanomas, particularly when found in the context of a CDK4 mutation/overexpression.
doi:10.1158/1535-7163.MCT-08-0431
PMCID: PMC2651569  PMID: 18790768
3.  Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts 
Breast Cancer Research  2005;7(6):R953-R964.
Introduction
Adjuvant breast cancer therapy significantly improves survival, but overtreatment and undertreatment are major problems. Breast cancer expression profiling has so far mainly been used to identify women with a poor prognosis as candidates for adjuvant therapy but without demonstrated value for therapy prediction.
Methods
We obtained the gene expression profiles of 159 population-derived breast cancer patients, and used hierarchical clustering to identify the signature associated with prognosis and impact of adjuvant therapies, defined as distant metastasis or death within 5 years. Independent datasets of 76 treated population-derived Swedish patients, 135 untreated population-derived Swedish patients and 78 Dutch patients were used for validation. The inclusion and exclusion criteria for the studies of population-derived Swedish patients were defined.
Results
Among the 159 patients, a subset of 64 genes was found to give an optimal separation of patients with good and poor outcomes. Hierarchical clustering revealed three subgroups: patients who did well with therapy, patients who did well without therapy, and patients that failed to benefit from given therapy. The expression profile gave significantly better prognostication (odds ratio, 4.19; P = 0.007) (breast cancer end-points odds ratio, 10.64) compared with the Elston–Ellis histological grading (odds ratio of grade 2 vs 1 and grade 3 vs 1, 2.81 and 3.32 respectively; P = 0.24 and 0.16), tumor stage (odds ratio of stage 2 vs 1 and stage 3 vs 1, 1.11 and 1.28; P = 0.83 and 0.68) and age (odds ratio, 0.11; P = 0.55). The risk groups were consistent and validated in the independent Swedish and Dutch data sets used with 211 and 78 patients, respectively.
Conclusion
We have identified discriminatory gene expression signatures working both on untreated and systematically treated primary breast cancer patients with the potential to spare them from adjuvant therapy.
doi:10.1186/bcr1325
PMCID: PMC1410752  PMID: 16280042

Results 1-3 (3)